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TWIRLS, a knowledge-mining technology, suggests a possible mechanism for the pathological changes in the human host after coronavirus infection via ACE2

文献类型：期刊论文

作者Ji, Xiaoyang1,2,3,4; Tan, Wenting5; Zhang, Chunming1,2,4,6; Zhai, Yubo2,8; Hsueh, Yiching1,2,4; Zhang, Zhonghai2; Zhang, Chunli4; Lu, Yanqiu7; Duan, Bo2,6; Tan, Guangming2,6
刊名DRUG DEVELOPMENT RESEARCH
出版日期2020-12-01
卷号81期号:8页码:1004-1018
ISSN号0272-4391
关键词coronavirus cytokine storm literature mining renin‐ angiotensin system topic inference
DOI10.1002/ddr.21717
英文摘要Faced with the current large-scale public health emergency, collecting, sorting, and analyzing biomedical information related to the "SARS-CoV-2" should be done as quickly as possible to gain a global perspective, which is a basic requirement for strengthening epidemic control capacity. However, for human researchers studying viruses and hosts, the vast amount of information available cannot be processed effectively and in a timely manner, particularly if our scientific understanding is also limited, which further lowers the information processing efficiency. We present TWIRLS (Topic-wise inference engine of massive biomedical literatures), a method that can deal with various scientific problems, such as liver cancer, acute myeloid leukemia, and so forth, which can automatically acquire, organize, and classify information. Additionally, this information can be combined with independent functional data sources to build an inference system via a machine-based approach, which can provide relevant knowledge to help human researchers quickly establish subject cognition and to make more effective decisions. Using TWIRLS, we automatically analyzed more than three million words in more than 14,000 literature articles in only 4 hr. We found that an important regulatory factor angiotensin-converting enzyme 2 (ACE2) may be involved in host pathological changes on binding to the coronavirus after infection. On triggering functional changes in ACE2/AT2R, the cytokine homeostasis regulation axis becomes imbalanced via the Renin-Angiotensin System and IP-10, leading to a cytokine storm. Through a preliminary analysis of blood indices of COVID-19 patients with a history of hypertension, we found that non-ARB (Angiotensin II receptor blockers) users had more symptoms of severe illness than ARB users. This suggests ARBs could potentially be used to treat acute lung injury caused by coronavirus infection.
WOS研究方向Pharmacology & Pharmacy
语种英语
出版者WILEY
WOS记录号WOS:000594633400010
源URL[http://119.78.100.204/handle/2XEOYT63/15951]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Na, Renhua; Deng, Guohong; Niu, Gang
作者单位1.Phil Rivers Technol Ltd, Joint Turing Darwin Lab, Beijing, Peoples R China
2.Chinese Acad Sci, Inst Comp Technol, Beijing, Peoples R China
3.Inner Mongolia Agr Univ, Breeding & Reprod Inner Mongolia Autonomous Reg C, Key Lab Anim Genet, Hohhot 010018, Peoples R China
4.Phil Rivers Technol Ltd, Dept Computat Biol, Beijing, Peoples R China
5.Third Mil Med Univ, Southwest Hosp, Dept Infect Dis, Army Med Univ, 29 Gaotanyan St, Chongqing 400038, Peoples R China
6.Chinese Acad Sci, West Inst Comp Technol, Chongqing, Peoples R China
7.Chongqing Publ Hlth Med Ctr, Dept Infect Dis, Chongqing, Peoples R China
8.Univ Chinese Acad Sci, Beijing, Peoples R China
推荐引用方式
GB/T 7714		 Ji, Xiaoyang,Tan, Wenting,Zhang, Chunming,et al. TWIRLS, a knowledge-mining technology, suggests a possible mechanism for the pathological changes in the human host after coronavirus infection via ACE2[J]. DRUG DEVELOPMENT RESEARCH,2020,81(8):1004-1018.
APA Ji, Xiaoyang.,Tan, Wenting.,Zhang, Chunming.,Zhai, Yubo.,Hsueh, Yiching.,...&Niu, Gang.(2020).TWIRLS, a knowledge-mining technology, suggests a possible mechanism for the pathological changes in the human host after coronavirus infection via ACE2.DRUG DEVELOPMENT RESEARCH,81(8),1004-1018.
MLA Ji, Xiaoyang,et al."TWIRLS, a knowledge-mining technology, suggests a possible mechanism for the pathological changes in the human host after coronavirus infection via ACE2".DRUG DEVELOPMENT RESEARCH 81.8(2020):1004-1018.

入库方式： OAI收割

来源：计算技术研究所

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